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Record W2161377480 · doi:10.1109/pes.2006.1709032

A predictive phase locked loop applicable to utility and non-utility AC power systems

2006· article· en· W2161377480 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venue2006 IEEE Power Engineering Society General Meeting · 2006
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHarmonicsAmplitudeComputer scienceControl theory (sociology)Electronic engineeringField-programmable gate arrayPhase-locked loopPower electronicsPhase noiseEngineeringElectrical engineeringVoltagePhysics

Abstract

fetched live from OpenAlex

A predictive phase locked loop (PPLL) suitable for applications in utility and non-utility power systems and power electronics is presented. The PPLL is frequency adaptive and can provide time variant information about the frequency and amplitude of the fundamental component of an input signal. The PPLL offers a high degree of immunity to wide-band noise, harmonics, inter-harmonics and impulse disturbances. Analytical methods for modeling the PPLL are developed to achieve high execution speed and low real-estate utilization. The mathematical properties of the analytical methods are presented. The PPLL is implemented on a field programmable gate array (FPGA). The locking range of the PPLL is from a fraction of Hz to a few kHz and from 3% to 100% of the nominal input amplitude. The worst case response time of the PPLL is 2 cycles of the input signal period for any realistic perturbation in frequency, amplitude, and/or phase angle. The proposed method is faster, more flexible and more robust than currently available methods

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.404
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.003
GPT teacher head0.190
Teacher spread0.186 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it